Risk and resilience in autism spectrum disorder: a missed translational opportunity?
Bibliographic record
Abstract
The objective of this review is to provide a narrative summary of risk and resiliency in autism spectrum disorder (ASD) over the lifespan. In recent years, much has been learned about risk factors for ASD which include both genetic and environmental mechanisms. Resiliency in ASD is much less studied but examples can be gleaned by exploring studies that allow for heterogeneity in causation and outcome. Possible examples come from the literature on sex difference, infant siblings, and natural history. Exciting translational opportunities can be achieved through a greater focus on understanding protective factors and resiliency in ASD than the field's almost exclusive focus on risk factors and the ability to predict poor outcomes. Although the exact nature of processes that protect in ASD are not yet known, putting a resiliency lens on research and clinical practice may prove illuminating. WHAT THIS PAPER ADDS: Resiliency in autism spectrum disorder is a function of the vast variation seen in etiology and outcome. A focus on strengthening protective factors may improve long-term outcome.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".